Open the Data Resource: https://gis.chesapeakebay.net/mpa/scenarioviewer/ This viewer provides basic mapping functionality for a subset of Public Reports for Load Scenarios available from the CAST Tool. It also contains map layers for several commonly requested data layers associated with the Chesapeake Bay suite of models.

description: USGS Imagery Only is a tile cache base map of orthoimagery in The National Map visible to the 1:18,000 scale. Orthoimagery data are typically high resolution images that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a planimetric map. USGS digital orthoimage resolution may vary from 6 inches to 1 meter. In the former resolution, every pixel in an orthoimage covers a six inch square of the earth's surface, while in the latter resolution, one meter square is represented by each pixel. Blue Marble: Next Generation source is displayed at small to medium scales. However, the majority of the imagery service source is from the National Agriculture Imagery Program (NAIP) for the conterminous United States. The data is 1-meter pixel resolution with "leaf-on". Collection of NAIP imagery is administered by the U.S. Department of Agriculture's Farm Service Agency (FSA). In areas where NAIP data is not available, other imagery may be acquired through partnerships by the USGS. The National Map program is working on acquisition of high resolution orthoimagery (HRO) for Alaska and Hawaii. Most of the new Alaska imagery data will not be available in this service due to license restrictions. The National Map viewer allows free downloads of public domain, 1-meter resolution orthoimagery in JPEG 2000 (jp2) format for the conterminous United States, with many urban areas and other locations at 1-foot (or better) resolution also in JPEG 2000 (jp2) format. For scales below 1:18,000, use the dynamic USGS Imagery Only Large service, https://services.nationalmap.gov/arcgis/rest/services/USGSImageOnlyLarge/MapServer.; abstract: USGS Imagery Only is a tile cache base map of orthoimagery in The National Map visible to the 1:18,000 scale. Orthoimagery data are typically high resolution images that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a planimetric map. USGS digital orthoimage resolution may vary from 6 inches to 1 meter. In the former resolution, every pixel in an orthoimage covers a six inch square of the earth's surface, while in the latter resolution, one meter square is represented by each pixel. Blue Marble: Next Generation source is displayed at small to medium scales. However, the majority of the imagery service source is from the National Agriculture Imagery Program (NAIP) for the conterminous United States. The data is 1-meter pixel resolution with "leaf-on". Collection of NAIP imagery is administered by the U.S. Department of Agriculture's Farm Service Agency (FSA). In areas where NAIP data is not available, other imagery may be acquired through partnerships by the USGS. The National Map program is working on acquisition of high resolution orthoimagery (HRO) for Alaska and Hawaii. Most of the new Alaska imagery data will not be available in this service due to license restrictions. The National Map viewer allows free downloads of public domain, 1-meter resolution orthoimagery in JPEG 2000 (jp2) format for the conterminous United States, with many urban areas and other locations at 1-foot (or better) resolution also in JPEG 2000 (jp2) format. For scales below 1:18,000, use the dynamic USGS Imagery Only Large service, https://services.nationalmap.gov/arcgis/rest/services/USGSImageOnlyLarge/MapServer.

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping effort is to produce high-resolution geologic maps and a Geographic Information System (GIS) project that presents images and grids of bathymetry, shaded relief bathymetry, and backscatter intensity data from these surveys that will serve the needs of research, management and the public.

Product Specifications Coverage: Partial coverage, predominantly in northern Australia, along major transport routes, and other selected areas. About 1000 maps have been published to date. Currency: Ranges from 1968 to 2006. Coordinates: Geographical and UTM. Datum: AGD66, new edition WGS84; AHD. Projection: Universal Transverse Mercator UTM. Medium: Paper, flat copies only.

description: This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer; abstract: This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

I am pleased to share the updated context map DRAFT for your review and comments.Of course, review to note any obvious omissions or anomalies in the map. Also, please share your general thoughts on the look and feel of the map. The way we have it right now with the basemap labeled “Light Gray Canvas”, the building footprints show up as you zoom in. I find that very helpful to visually confirm the context.There are actually have many different criteria that can lead to classification. This detail was necessary to refine the map. You can check on and off the different criteria on the left to see how it impacts the map if you would like.There are many different considerations, but mostly context is defined by the development of buildings - how close the buildings are to the road, how densely they have been built together, and how large the building area is. Urban and Rural Village contexts tend to have more buildings close to the road and suburban contexts tend to have buildings further back. Here is the primary data considered: Immediate Building Density Immediate Building Area Density Immediate Building Count Wide Building Density Wide Building Area Density Wide Intersection Density Wide Segment Density Federal and State Urban Compact AreasThe “immediate” building information considers buildings that partially within 60 feet of the road centerline. For a sports analogy, that is about the distance from a baseball pitching rubber to home plate. The “wide” data looks at buildings, segments, and intersections in the general area 1/8 of a mile from centerline in all directions. That is about the distance of two football fields. Both types of data have value, especially when they are strategically used together.The Map is split into 5 contexts categories: Red - Urban Orange - Suburban Dark Green - Rural Village (Heavily Developed) Light Green - Rural Village (Moderately Developed) Blank – RuralThe red urban and the dark green village areas have exactly the same criteria except one is inside federal or state urban compact and one is outside both urban compacts. You will also notice some of the major arterial roads cutting through urban areas have been identified as suburban. Examples of this include William Clark Drive in Westbrook, Center Street and Minot Avenue in Auburn, and Pleasant Street in Brunswick. This typically occurs because the buildings are mostly built back further from the road.Important to note: We will need two “rural village” layers. We realized we need to separate how we treat the very densely developed villages like downtown Camden and the fringe villages like Searsmont and Jefferson.

Thank you for giving this map a look over and providing your feedback.

Montana FWP fishing access sites region 6 printable map 36x18 for Montana FWP Printable Map Catalog. Maps will be regularly updated as data updates occur.

This report presents in tabular form a complete listing of faunal and minor floral elements, along with their identification as known to date, for all fossils collected by field party members of the Alaska Division of Geological & Geophysical Surveys (DGGS) during their 1997 and 1998 geological mapping effort in the Healy A-6 Quadrangle. In addition, all known U.S. Geological Survey fossil localities that could be located from previously published maps are also shown on the fossil locality map and listed in the fossil register.

Contained within the 3rd Edition (1957) of the Atlas of Canada is a plate that shows six maps of cities or towns at different scales. The portions of all, but the first and last of the maps, illustrate the principal national map series produced by the Surveys and Mapping Branch of the Department of Mines and Technical Surveys [now Natural Resources Canada], circa 1958.

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

Montana warden districts region 6 printable map 8.5x11 for Montana FWP Printable Map Catalog. Maps will be regularly updated as data updates occur.

description: Environmental Modeling dataset current as of unknown. Six suitable maps (natural values, working forests, farmland, residential, commercial, industrial) for an eleven county region..; abstract: Environmental Modeling dataset current as of unknown. Six suitable maps (natural values, working forests, farmland, residential, commercial, industrial) for an eleven county region..

Accurate and precise measurements of global cropland extent are needed for monitoring the sustainability of agriculture at all scales. Recent advancement in remote sensing and land cover mapping methods have greatly increased the ability to estimate cropland area distribution and trends. Here the FAO presents a map of cropland agreement produced by consolidating information at pixel level from six high-resolutions maps for circa 2020. The following six high resolution layers were used: ESRI 10 meter LU/LC, FROM-GLC, GLAD, GLC-FCS30, Globeland30 and Worldcover.

Two bands are included in the dataset:

Simple agreement (values between 1 and 6)

Detailed agreement (values between 1 and 63)

The map, developed in the Google Earth Engine platform, combines the 6 land cover/cropland layers to show their cropland agreement on pixel level at a spatial resolution of 30 meters. The simple agreement has pixel values that range from 1 (only 1 dataset classifies as cropland) to 6 (all datasets agree on presence of cropland). Pixels with a value of 0 indicate pixels where all datasets agree on absence of cropland. The second band includes a detailed agreement, showing which combination of the 6 datasets classify a pixel as cropland. The overview table (DetailedAgreement_LookupTable.xlsx) shows what the pixel values of this detailed agreement (from 1 to 63) correspond to.

The dataset has been uploaded in 16 tiles, in the preview below and in the file "ACroplandAgreement_30m_Tiles.png" the extent of each tile can be found.

For more information on FAO statistics on land cover and land use:

FAO. 2022. Land use statistics and indicators. Global, regional and country trends, 2000–2020. FAOSTAT Analytical Brief, no. 48. Rome. https://doi.org/10.4060/cc0963en

FAO. 2021. Land cover statistics. Global, regional and country trends, 2000–2019. FAOSTAT Analytical Brief Series No. 37. Rome.

The topographic maps referred to as the Issue State (AS) were primarily intended for military use and were classified as Confidential Classified. Content levels of the TK50 AS are: Ground plan/grid-black, water-blue, relief/street filling/development areas-red-brown, forest areas-green.

The product represents a new design of the State Map at a scale of 1:5,000 in raster form, whose advantages are recency and colour processing. The map contains planimetry based on cadastral map, altimetry adopted from the altimetry part of ZABAGED and map lettering based on database of geographic names Geonames and abbreviations of feature type signification coming up from attributes of selected ZABAGED features. The cartographic visualisation is solved automatically without manual works of a cartographer. This new design of the SM 5 is repeatedly generated once a year on the part of the Czech territory where the vector form of cadastral map is available. Therefore, part of export units (map sheets of SM 5) has not a full coverage (price of such export unit is then proportionally reduced).

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping effort is to produce high-resolution geologic maps and a Geographic Information System (GIS) project that presents images and grids of bathymetry, shaded relief bathymetry, and backscatter intensity data from these surveys that will serve the needs of research, management and the public.

Judicial Subdistrict 6 Precinct Map Book - 2022

The topographic maps referred to as the Issue State (AS) were primarily intended for military use and were classified as Confidential Classified. On a scale of 1: 25,000 there were 2 output variants: TK=topographic maps and TSP=topographic city maps.

URL: https://geoscience.data.qld.gov.au/dataset/mr009481

The QUEENSLAND MAPSHEET 2, 4, 6, 12 AND 16 MILE MAP INDEX Index map was published in 1969 at 80 miles to an Inch as part of the STATE MAP series to administer permit and permit related spatial information. The map was maintained internally as a provisional office chart.
The map product is available to all government agencies, industry and the public for reference.
Title and Image reference number is QUEENSLAND MAPSHEET 2, 4, 6, 12 AND 16 MILE MAP INDEX_7453.

2 Mile, 4 Mile (old series), 4 mile (new series), 12 Mile Tenure sheets, 16 mile, 16 Mile Stock routes, 4 Mile & 6 Mile Moreton District maps